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European Conference on Parallel Processing

Euro-Par 2011: Euro-Par 2011: Parallel Processing Workshops pp 43–52Cite as

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Distributed Management and Analysis of Omics Data

Distributed Management and Analysis of Omics Data

  • Mario Cannataro30 &
  • Pietro Hiram Guzzi30 
  • Conference paper
  • 1062 Accesses

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7156)

Abstract

The omics term refers to different biology disciplines such as, for instance, genomics, proteomics, or interactomics. The suffix -ome is used to indicate the objects of study of such disciplines, such as the genome, proteome, or interactome, and usually refers to a totality of some sort. This paper introduces omics data and the main computational techniques for their storage, preprocessing and analysis. The increasing availability of omics data due to the advent of high throughput technologies poses novel issues on data management and analysis that can be faced by parallel and distributed storage systems and algorithms. After a survey of main omics databases, preprocessing techniques and analysis approaches, the paper describes some recent bioinformatics tools in genomics, proteomics and interactomics that use a distributed approach.

Keywords

  • Omics Data
  • Genomics
  • Proteomics
  • Interactomics
  • Distributed Computing

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Author information

Authors and Affiliations

  1. Department of Medical and Surgical Sciences, Bioinformatics Laboratory, University Magna Græcia of Catanzaro, 88100, Catanzaro, Italy

    Mario Cannataro & Pietro Hiram Guzzi

Authors
  1. Mario Cannataro
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  2. Pietro Hiram Guzzi
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Editor information

Editors and Affiliations

  1. Scilytics, Koellnerhofgasse 3/15A, 1010, Vienna, Austria

    Michael Alexander

  2. ICAR-CNR, Via P. Castellino, 111, 80131, Napoli, Italy

    Pasqua D’Ambra

  3. University of Amsterdam, 1090, Amsterdam, Netherlands

    Adam Belloum

  4. Innovative Computing Laboratory, The University of Tennessee, US

    George Bosilca

  5. Department of Experimental Medicine and Clinic, University Magna Græcia, 88100, Catanzaro, Italy

    Mario Cannataro

  6. Computer Science Department, University of Pisa, Italy

    Marco Danelutto

  7. Second University of Naples, Italy

    Beniamino Di Martino

  8. TUMünchen,, Boltzmannstr. 3, ,, 85748, Garching, Germany

    Michael Gerndt

  9. Equipe Runtime, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Emmanuel Jeannot & Raymond Namyst & 

  10. Equipe HIEPACS, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Jean Roman

  11. Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831-6164, Oak Ridge, TN, USA

    Stephen L. Scott

  12. Department of Scientific Computing, University of Vienna, Nordbergstr. 15/3C, 1090, Vienna, Austria

    Jesper Larsson Traff

  13. Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831, Oak Ridge, TN, USA

    Geoffroy Vallée

  14. Technische Universität München, Germany

    Josef Weidendorfer

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Cannataro, M., Guzzi, P.H. (2012). Distributed Management and Analysis of Omics Data. In: Alexander, M., et al. Euro-Par 2011: Parallel Processing Workshops. Euro-Par 2011. Lecture Notes in Computer Science, vol 7156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29740-3_6

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  • DOI: https://doi.org/10.1007/978-3-642-29740-3_6

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  • Print ISBN: 978-3-642-29739-7

  • Online ISBN: 978-3-642-29740-3

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